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    <title>topic Re: Repairable system failure prediction in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Repairable-system-failure-prediction/m-p/630673#M82887</link>
    <description>&lt;P&gt;To clarify, after modeling the lifetime data, the model will predict the time at which the probability of failure is a given level or the probability of failure at a given time. Both predictions are generally extrapolations beyond observed events. They incur wide confidence intervals.&lt;/P&gt;</description>
    <pubDate>Wed, 10 May 2023 18:18:06 GMT</pubDate>
    <dc:creator>Mark_Bailey</dc:creator>
    <dc:date>2023-05-10T18:18:06Z</dc:date>
    <item>
      <title>Repairable system failure prediction</title>
      <link>https://community.jmp.com/t5/Discussions/Repairable-system-failure-prediction/m-p/630336#M82850</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;Here is a general question for JMP experts:&lt;BR /&gt;say I have data on a system that fails with various failure modes. The data contains dates of repair on each components repair. I I know how to analyze this data for reliability as shown in video here:&lt;BR /&gt;&lt;A href="https://community.jmp.com/t5/Mastering-JMP/Analyzing-Reliability-for-Repairable-Systems/ta-p/483465" target="_blank"&gt;https://community.jmp.com/t5/Mastering-JMP/Analyzing-Reliability-for-Repairable-Systems/ta-p/483465&lt;/A&gt;&lt;/P&gt;&lt;P&gt;However what I am interested is in predicting the time at which the system will fail in the future and the probability of that failure.&lt;/P&gt;&lt;P&gt;Any idea/suggestion on how to do that in JMP?&lt;BR /&gt;Thanks,&lt;BR /&gt;&lt;BR /&gt;&lt;/P&gt;</description>
      <pubDate>Tue, 09 May 2023 19:59:40 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Repairable-system-failure-prediction/m-p/630336#M82850</guid>
      <dc:creator>MarkovVaribles1</dc:creator>
      <dc:date>2023-05-09T19:59:40Z</dc:date>
    </item>
    <item>
      <title>Re: Repairable system failure prediction</title>
      <link>https://community.jmp.com/t5/Discussions/Repairable-system-failure-prediction/m-p/630636#M82881</link>
      <description>&lt;P&gt;I'm not an expert in repairable systems, but I'll offer two suggestions as a catalyst for further discussion (and to keep your post from falling off the front page with 0 replies):&lt;/P&gt;
&lt;OL&gt;
&lt;LI&gt;Use the MTBF and Failure Intensity Profilers in the Reliability Growth platform as proxies for "time at which the system will fail and probability of failure". &lt;A href="https://reliawiki.org/index.php/RGA_Overview#Terminology" target="_self"&gt;This link&lt;/A&gt; suggests that this is standard practice for repairable systems.
&lt;OL&gt;
&lt;LI&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Jed_Campbell_0-1683733092355.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/52694i3427FD6EABF1C667/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Jed_Campbell_0-1683733092355.png" alt="Jed_Campbell_0-1683733092355.png" /&gt;&lt;/span&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;/LI&gt;
&lt;/OL&gt;
&lt;/LI&gt;
&lt;LI&gt;(Perhaps not as statistically rigorous) If you hide and exclude any rows in your data that include 0 fixes, then you could treat the data as a non-repairable system and use the Life Distribution Profilers to model time (Distribution, Quantile, Density) and probability (Hazard Profile) of failures.
&lt;OL&gt;
&lt;LI&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Jed_Campbell_1-1683733515191.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/52696i3B24F665CBED5184/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Jed_Campbell_1-1683733515191.png" alt="Jed_Campbell_1-1683733515191.png" /&gt;&lt;/span&gt;&lt;/LI&gt;
&lt;/OL&gt;
&lt;/LI&gt;
&lt;/OL&gt;
&lt;P&gt;I've attached a sample dataset with scripts for both of these approaches saved to the table.&lt;/P&gt;</description>
      <pubDate>Wed, 10 May 2023 15:47:30 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Repairable-system-failure-prediction/m-p/630636#M82881</guid>
      <dc:creator>Jed_Campbell</dc:creator>
      <dc:date>2023-05-10T15:47:30Z</dc:date>
    </item>
    <item>
      <title>Re: Repairable system failure prediction</title>
      <link>https://community.jmp.com/t5/Discussions/Repairable-system-failure-prediction/m-p/630673#M82887</link>
      <description>&lt;P&gt;To clarify, after modeling the lifetime data, the model will predict the time at which the probability of failure is a given level or the probability of failure at a given time. Both predictions are generally extrapolations beyond observed events. They incur wide confidence intervals.&lt;/P&gt;</description>
      <pubDate>Wed, 10 May 2023 18:18:06 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Repairable-system-failure-prediction/m-p/630673#M82887</guid>
      <dc:creator>Mark_Bailey</dc:creator>
      <dc:date>2023-05-10T18:18:06Z</dc:date>
    </item>
    <item>
      <title>Re: Repairable system failure prediction</title>
      <link>https://community.jmp.com/t5/Discussions/Repairable-system-failure-prediction/m-p/888720#M105107</link>
      <description>&lt;P&gt;Hello JMP Team,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Has there been a more direct method to compute this "time to next failure"?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Given, that we have outputs such as growth and scale parameters from NHPP or Crow AMSAA models?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Thanks.&lt;/P&gt;</description>
      <pubDate>Wed, 23 Jul 2025 12:22:32 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Repairable-system-failure-prediction/m-p/888720#M105107</guid>
      <dc:creator>OPersaud</dc:creator>
      <dc:date>2025-07-23T12:22:32Z</dc:date>
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